The widespread use of digital cameras and camera phones, combined with the portability and vast storage capabilities offered by this type of media capture device, makes it possible for people to capture and store as many photographs as they want at any time and in any place. The size of image collections has increased dramatically as a result, and organizing digital photographs is becoming an increasingly difficult task. Therefore, an intelligent and effective image classification method is desirable. One approach involves photo annotation and tagging. However, the manual addition of tags is still a cumbersome and time-consuming task for users.
Efforts have therefore been made to provide automatic tagging suggestions by identifying the tags applied to similar photographs or videos. However, existing approaches do not include the user in the loop. There is no successful solution that integrates user-feedback to improve the efficiency of automatic tag generation.